Natural Selection on Quantitative Traits in the Bombina Hybrid Zone

Evolution ◽  
1995 ◽  
Vol 49 (6) ◽  
pp. 1224 ◽  
Author(s):  
Beate Nurnberger ◽  
Nick Barton ◽  
Catriona MacCallum ◽  
Jason Gilchrist ◽  
Michael Appleby
Keyword(s):  
Natural Selection ◽  
Hybrid Zone ◽  
Quantitative Traits

scholarly journals NATURAL SELECTION ON QUANTITATIVE TRAITS IN THE BOMBINA HYBRID ZONE

Evolution ◽  
1995 ◽  
Vol 49 (6) ◽  
pp. 1224-1238 ◽  
Author(s):  
Beate Nürnberger ◽  
Nick Barton ◽  
Catriona MacCallum ◽  
Jason Gilchrist ◽  
Michael Appleby
Keyword(s):  
Natural Selection ◽  
Hybrid Zone ◽  
Quantitative Traits

scholarly journals Spontaneous mutations and the origin and maintenance of quantitative genetic variation

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Wen Huang ◽  
Richard F Lyman ◽  
Rachel A Lyman ◽  
Mary Anna Carbone ◽  
Susan T Harbison ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Quantitative Traits ◽  
Spontaneous Mutation ◽  
Natural Populations ◽  
Empirical Work ◽  
Stabilizing Selection ◽  
Spontaneous Mutation Rate ◽  
Evolutionary Forces ◽  
Quantitative Genetic

Mutation and natural selection shape the genetic variation in natural populations. Here, we directly estimated the spontaneous mutation rate by sequencing new Drosophila mutation accumulation lines maintained with minimal natural selection. We inferred strong stabilizing natural selection on quantitative traits because genetic variation among wild-derived inbred lines was much lower than predicted from a neutral model and the mutational effects were much larger than allelic effects of standing polymorphisms. Stabilizing selection could act directly on the traits, or indirectly from pleiotropic effects on fitness. However, our data are not consistent with simple models of mutation-stabilizing selection balance; therefore, further empirical work is needed to assess the balance of evolutionary forces responsible for quantitative genetic variation.

Strong Natural Selection in a Warning-Color Hybrid Zone

Evolution ◽  
1989 ◽  
Vol 43 (2) ◽  
pp. 421 ◽  
Author(s):  
James Mallet ◽  
Nicholas H. Barton
Keyword(s):  
Natural Selection ◽  
Hybrid Zone

Chromosomal and allelic variation in Drosophila americana: selective maintenance of a chromosomal cline

Genome ◽  
2002 ◽  
Vol 45 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Bryant F McAllister
Keyword(s):  
Natural Selection ◽  
Hybrid Zone ◽  
Allelic Variation ◽  
Natural Populations ◽  
Chromosomal Evolution ◽  
Geographic Region ◽  
Hybrid Zones ◽  
Geographic Structure ◽  
Latitudinal Transect ◽  
Selective Maintenance

Geographically structured genetic variation, as represented by clines and hybrid zones, offers unique opportunities to study adaptation and speciation in natural populations. A hybrid zone has been reported between Drosophila americana americana and Drosophila americana texana, two taxa that are distinguished solely by the arrangement of their X and 4th chromosomes. In this study, samples of D. americana were collected along a latitudinal transect across the inferred hybrid zone, and the frequency of the alternative chromosomal arrangements is reported. These data illustrate that the alternative chromosomal arrangements are distributed along a shallow cline over a broad geographic region, and that the frequency of the arrangements is tightly correlated with latitude. Allelic variants at 13 RFLP loci in three genes on chromosome 4 exhibit no evidence of association with the cline. Presence of a cline for the chromosomal arrangements, as well as a general absence of geographic structure for variation at these genes, is interpreted as evidence that natural selection is responsible for the maintenance of this chromosomal cline. Furthermore, these results demonstrate that taxonomic subdivision of D. americana is unwarranted, because it exists as a cohesive species that is segregating a chromosomal fusion.Key words: chromosomal evolution, Robertsonian fusion, hybrid zone, cline, geographic variation, natural selection.

THE EFFECT OF LOCATION ON NATURAL SELECTION IN BULK POPULATIONS OF BARLEY (HORDEUM VULGARE L.). II. QUANTITATIVE TRAITS

1980 ◽  
Vol 60 (1) ◽  
pp. 41-47 ◽  
Author(s):  
T. M. CHOO ◽  
H. R. KLINCK ◽  
C. A. ST-PIERRE
Keyword(s):  
Natural Selection ◽  
Quantitative Traits ◽  
Bulk Material ◽  
Flag Leaf ◽  
Selection Procedure ◽  
Distinct Pattern ◽  
Rate Of Change ◽  
Hordeum Vulgare L ◽  
Testing Environments ◽  
Segregating Population

The effects of natural selection on quantitative traits were compared in 17 single hybrid barley populations which had been developed either by growing the bulk material continuously in each of two locations, Macdonald College and La Pocatière, or by alternating between these locations annually or after 2–8 yr per location. Comparisons were made by testing the F10 and F15 generations of each of the 17 populations at the two locations for 2 yr. Natural selection favored longer awns, shorter spikes, smaller flag leaves, fewer spikes per plot, and, perhaps, heavier grains. Natural selection had very little effect, however, on the number of grains per spike or grain yield. Variation among populations was observed only for awn length, spike length, flag leaf area, and number of grains per spike in the F15 generation. This indicates that the rate of change for the four traits was affected by the propagation environments but was not affected by the frequency of alternation because no distinct pattern was found among these populations. These populations in both generations responded similarly to the testing environments except for awn length in F15. It is suggested that wider diversity of locality is needed in order to evaluate effectively the usefulness of a natural selection procedure involving the alternating of a segregating population.

Assortative Mating and Natural Selection in an Iris Hybrid Zone

Evolution ◽  
1994 ◽  
Vol 48 (6) ◽  
pp. 1946 ◽  
Author(s):  
Mitchell B. Cruzan ◽  
Michael L. Arnold
Keyword(s):  
Natural Selection ◽  
Assortative Mating ◽  
Hybrid Zone

scholarly journals Deciphering signatures of natural selection via deep learning

2021 ◽  
Author(s):  
Xinghu Qin ◽  
Charleston W.K. Chiang ◽  
Oscar E Gaggiotti
Keyword(s):  
Deep Learning ◽  
Natural Selection ◽  
Quantitative Traits ◽  
Predictive Power ◽  
Spatial Location ◽  
Human Genetic Variation ◽  
Environmental Attributes ◽  
Wide Range ◽  
Candidate Regions ◽  
Genomic Regions

Identifying genomic regions influenced by natural selection provides fundamental insights into a wide range of problems including human health, animal and plant breeding, and the understanding of local adaptation. We propose a new method, DeepGenomeScan, that can be used to address all these problems. It is based on the principle that the genotypes of individuals can be used to predict any associated trait; not only their phenotype but also their spatial location or the environmental attributes of the habitat they live in. We, therefore,implemented a deep learning method to detect candidate regions under selection by identifying loci that contribute the most to the predictive power of the deep neural network. Using simulations, we show that our method can successfully identify loci underlying quantitative traits subject to complex spatial patterns of selection. We apply DeepGenomeScan to a European human genetic variation dataset and posit that the loci that contribute the most to the prediction of latitude and longitude are located in genomic regions under selection. Using this approach, we identified many SNPs located within well-known genes, some of which were not identified using existing population genetics approaches, e.g. MCM6, MGAT5, TMEM163.

scholarly journals RELATIVE CONTRIBUTION OF DISPERSAL AND NATURAL SELECTION TO THE MAINTENANCE OF A HYBRID ZONE IN LITTORINA

Evolution ◽  
2004 ◽  
Vol 58 (12) ◽  
pp. 2734-2746 ◽  
Author(s):  
Raquel Cruz ◽  
Carlos Vilas ◽  
Javier Mosquera ◽  
Carlos García
Keyword(s):  
Natural Selection ◽  
Hybrid Zone ◽  
Relative Contribution

scholarly journals Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing among full-sibs

2021 ◽  
Author(s):  
Antoine Fraimout ◽  
Zitong Li ◽  
Mikko J. Sillanpää ◽  
Pasi Rastas ◽  
Juha Merilä
Keyword(s):  
Natural Selection ◽  
Variance Components ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Identity By Descent ◽  
Quantitative Genetic ◽  
Genome Wide ◽  
Quantitative Genetic Parameters

ABSTRACTAdditive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most wild animal populations. Using estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci, we estimated quantitative genetic parameters for traits known to be under directional natural selection in nine-spined sticklebacks (Pungitius pungitius) and compared these to traditional pedigree-based estimators. Using four different datasets, with varying sample sizes and pedigree complexity, we further assessed the performance of different Genomic Relationship Matrices (GRM) to estimate additive and dominance variance components. Large variance in IBD relationships allowed accurate estimation of genetic variance components, and revealed significant heritability for all measured traits, with negligible dominance contributions. Genome-partitioning analyses revealed that all traits have a polygenic basis and are controlled by genes at multiple chromosomes. The results demonstrate how large full-sib families of highly fecund vertebrates can be used to obtain accurate estimates quantitative genetic parameters to provide insights on genetic architecture of quantitative traits in non-model organisms from the wild. This approach should be particularly useful for studies requiring estimates of genetic variance components from multiple populations as for instance when aiming to infer the role of natural selection as a cause for population differentiation in quantitative traits.

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